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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-science-and-machine-learning-fundamentals-one/
课程评论:没有评论
课程名称:数据科学与机器学习基础 [2025] 概述:本课程通过实践性很强的方式,深入探讨数据科学和机器学习的基础。数据科学和机器学习正在快速发展,其算法在社会、互联网和科技的各个层面上都发挥着重要作用,分析和优化我们生活、商业和社会的方方面面。本课程将涵盖数据科学和机器学习的基础知识,面向初学者和有经验的数据科学家,力求成为Udemy课程中教育价值最高的选择。 学习内容包括但不限于: 1. **使用监督学习进行回归与预测**:学习线性回归到多元多项式回归模型的构建和应用。 2. **邮件分类的机器学习模型**:深入理解分类过程、分类理论和可视化,学习强大的随机森林分类器和投票分类器模型。 3. **基于无监督学习的聚类分析**:掌握聚类理论和探索性数据分析,使用多种聚类算法,包括层次聚类和基于密度的聚类。 4. **数据科学与机器学习的基础知识**:为从事相关工作或学习奠定坚实的基础。 5. **高级人工智能预测模型与自动建模**:学习强大的算法实现模型的自动创建。 6. **文本挖掘与自动化**:掌握文本数据挖掘的基本知识,如分词、文本准备、拼写检查和情感挖掘等。 7. **掌握Python与Pandas**:提供易于理解的Python和Pandas数据处理教程,适合所有编程水平的学习者。 8. **云计算的应用**:学习如何使用Anaconda云笔记本,搭建Python数据科学和机器学习环境的本地安装。 课程旨在为每位学习者提供丰富的独特内容,使他们能够独立自信地执行数据科学与机器学习的常见任务。课程要求掌握四则运算以及对Windows、Linux或Mac OS等操作系统有基本了解。完成课程后,学员将掌握数据科学与机器学习的理论、算法、方法和最佳实践,具备扎实的实践知识。
This course is an exciting hands-on view of the fundamentals of Data Science and Machine LearningData Science and Machine Learning are developing on a massive scale. Everywhere you look in society, the world wide web, or in technology, you will find Data Science and Machine Learning algorithms working behind the scenes to analyze and optimize all aspects of our lives, businesses, and our society. Data Science and Machine Learning with Artificial Intelligence are some of the hottest and fastest-developing areas right now. This course will teach you the fundamentals of Data Science and Machine Learning. This course has exclusive content that will teach you many new things regardless of if you are a beginner or an experienced Data Scientist, and aspires to be one of the best Udemy courses in terms of education and value. You will learn aboutRegression and Prediction with Machine Learning models using supervised learning. This course has the most complete and fundamental master-level regression analysis content packages on Udemy, with hands-on, useful practical theory, and automatic Machine Learning algorithms for model building, feature selection, and artificial intelligence. You will learn about models ranging from linear regression models to advanced multivariate polynomial regression models.Classification with Machine Learning models using supervised learning. You will learn about the classification process, classification theory, and visualizations as well as some useful classifier models, including the very powerful Random Forest Classifier Ensembles and Voting Classifier Ensembles.Cluster Analysis with Machine Learning models using unsupervised learning. In this part of the course, you will learn about unsupervised learning, cluster theory, artificial intelligence, explorative data analysis, and seven useful Machine Learning clustering algorithms ranging from hierarchical cluster models to density-based cluster models.The fundamentals of Data Science and Machine Learning. This course gives a very solid foundation and knowledge base for Data Science and Machine Learning jobs or studies.Advanced A.I. prediction models and automatic model creation. This video course includes videos where the use of very powerful algorithms for automatic model creation is taught.Advanced Text Mining and Automation. You will learn to mine text data and the fundamentals of Text and Emotion Mining such as Tokenization, text data preparation, spell checking, lemmatization, stemming, and classification of text data. Mastering Python for data handling.Mastering Pandas for data handling.This course includesa comprehensive and easy-to-follow teaching package for Mastering Python and Pandas for data handling, which makes anyone able to learn the course contents regardless of beforehand knowledge of programming, tabulation software, Python, Pandas, Data Science, or Machine Learning.Learn to use Cloud computing: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resourcesan optional easy-to-follow guide for downloading, installing, and setting up the Anaconda Distribution, which makes anyone able create a local installation of a Python Data Science and Machine Learning environment.content that will teach you many new things, regardless of if you are a beginner or an experienced Data Scientist.a large collection of unique content, and will teach you many new things that only can be learned from this course on Udemy.A complete masterclass package for Data Science and Machine Learning.A course structure built on a proven and professional framework for learning.A compact course structure and no killing time.Is this course for you?This course is for you, regardless if you are a beginner or an experienced Data Scientist. This course is for you, regardless if you have no education or are experienced with a Ph.D.Course requirementsThe four ways of counting (+-*/)Basic everyday experience with either Windows, Linux, Mac OS, or similar operating systemsAfter completing this course, you will haveKnowledge about Data Science and Machine Learning theory, algorithms, methods, best practices, and tasks.Deep hands-on knowledge of Data Science and Machine Learning, and know how to do common Data Science and Machine Learning tasks.The ability to handle common Data Science and Machine Learning tasks with confidence.Knowledge to Master Python for Data Handling.Knowledge to Master Pandas for Data Handling.Knowledge and practical hands-on knowledge of Scikit-learn, Stats models, Matplotlib, Seaborn, and many other Python libraries.Detailed and deep Master knowledge of Regression Prediction, Classification, and Cluster Analysis.Advanced knowledge of A.I. prediction models and automatic model creation.Advanced Knowledge of Text Mining, Text Mining Tasks, and Emotion Mining.